Efficiently irrational: deciphering the riddle of human choice

Early versus late noise differentially enhances or degrades context-dependent choice

Noise is a fundamental problem for information processing in neural systems. In decision-making, noise is thought to cause stochastic errors in choice. However, little is known about how noise arising from different sources may contribute differently to value coding and choice behaviors. Here, we examine how noise arising early versus late in the decision process differentially impacts context-dependent choice behavior. We find in model simulations that under early noise, contextual information enhances choice accuracy, while under late noise, context degrades choice accuracy. Furthermore, we verify these opposing predictions in experimental human choice behavior. Manipulating early and late noise - by inducing uncertainty in option values and controlling time pressure - produces dissociable positive and negative context effects. These findings reconcile controversial experimental findings in the literature, suggesting a unified mechanism for context-dependent choice. More broadly, these findings highlight how different sources of noise can interact with neural computations to differentially modulate behavior.

People display consistent recency and primacy effects in behavior and neural activity across perceptual and value-based judgments

Retrospective judgments require decision-makers to gather information over time and integrate that information into a summary statistic like the average. Many retrospective judgments require putting equal weight on early and late information, in contrast to prospective judgments that involve predicting the future and so rely more on late information. We investigate how people weight information over time when continuously reporting the average stimulus strength in a sequence of displays. We investigate the consistency of these temporal profiles across perceptual and value-based tasks using both behavior and functional magnetic resonance imaging (fMRI) data. We found that people display remarkably consistent temporal weighting functions across choice domains, with a generally strong recency bias and modest primacy bias. The fMRI data revealed evidence-tracking activity in the cuneus in both tasks and in the left dorsolateral prefrontal cortex in the value-based task. Finally, a network of cognitive control regions is more active for people who exhibit a stronger primacy vs. recency bias. Together, our behavioral findings indicate that people consistently overweight recency when evaluating past information, and the neural data suggest that overcoming this tendency may require cognitive control.

The Relationship Among Range Adaptation, Social Anhedonia, and Social Functioning: A Combined Magnetic Resonance Spectroscopy and Resting-State fMRI Study

BACKGROUND AND HYPOTHESIS

Social anhedonia is a core feature of schizotypy and correlates significantly with social functioning and range adaptation. Range adaptation refers to representing a stimulus value based on its relative position in the range of pre-experienced values. This study aimed to examine the resting-state neural correlates of range adaptation and its associations with social anhedonia and social functioning.

STUDY DESIGN

In study 1, 60 participants completed resting-state magnetic resonance spectroscopy and fMRI scans. Range adaptation was assessed by a valid effort-based decision-making paradigm. Self-reported questionnaires was used to measure social anhedonia and social functioning. Study 2 utilized 26 pairs of participants with high (HSoA) and low levels of social anhedonia (LSoA) to examine the group difference in range adaptation's neural correlates and its relationship with social anhedonia and social functioning. An independent sample of 40 pairs of HSoA and LSoA was used to verify the findings.

STUDY RESULTS

Study 1 showed that range adaptation correlated with excitation-inhibition balance (EIB) and ventral prefrontal cortex (vPFC) functional connectivity, which in turn correlating positively with social functioning. Range adaptation was specifically determined by the EIB via mediation of ventral-medial prefrontal cortex functional connectivities. Study 2 found HSoA and LSoA participants exhibiting comparable EIB and vPFC connectivities. However, EIB and vPFC connectivities were negatively correlated with social anhedonia and social functioning in HSoA participants.

CONCLUSIONS

EIB and vPFC functional connectivity is putative neural correlates for range adaptation. Such neural correlates are associated with social anhedonia and social functioning.

Social implications of coexistence of CAVs and human drivers in the context of route choice

Suppose in a stable urban traffic system populated only by human driven vehicles (HDVs), a given proportion (e.g. [Formula: see text]) is replaced by a fleet of Connected and Autonomous Vehicles (CAVs), which share information and pursue a collective goal. Suppose these vehicles are centrally coordinated and differ from HDVs only by their collective capacities allowing them to make more efficient routing decisions before the travel on a given day begins. Suppose there is a choice between two routes and every day each driver makes a decision which route to take. Human drivers maximize their utility. CAVs might optimize different goals, such as the total travel time of the fleet. We show that in this plausible futuristic setting, the strategy CAVs are allowed to adopt may result in human drivers either benefitting or being systematically disadvantaged and urban networks becoming more or less optimal. Consequently, some regulatory measures might become indispensable.

Origins of noise in both improving and degrading decision making

Noise is a fundamental problem for information processing in neural systems. In decision-making, noise is thought to cause stochastic errors in choice. However, little is known about how noise arising from different sources may contribute differently to value coding and choice behaviors. Here, we examine how noise arising early versus late in the decision process differentially impacts context-dependent choice behavior. We find in model simulations that under early noise, contextual information enhances choice accuracy, while under late noise, context degrades choice accuracy. Furthermore, we verify these opposing predictions in experimental human choice behavior. Manipulating early and late noise - by inducing uncertainty in option values and controlling time pressure - produces dissociable positive and negative context effects. These findings reconcile controversial experimental findings in the literature, suggesting a unified mechanism for context-dependent choice. More broadly, these findings highlight how different sources of noise can interact with neural computations to differentially modulate behavior.

Significance

The current study addresses the role of noise origin in decision-making, reconciling controversies around how decision-making is impacted by context. We demonstrate that different types of noise - either arising early during evaluation or late during option comparison - leads to distinct results: with early noise, context enhances choice accuracy, while with late noise, context impairs it. Understanding these dynamics offers potential strategies for improving decision-making in noisy environments and refining existing neural computation models. Overall, our findings advance our understanding of how neural systems handle noise in essential cognitive tasks, suggest a beneficial role for contextual modulation under certain conditions, and highlight the profound implications of noise structure in decision-making.

Rationality, preferences, and emotions with biological constraints: it all starts from our senses

Is the role of our sensory systems to represent the physical world as accurately as possible? If so, are our preferences and emotions, often deemed irrational, decoupled from these 'ground-truth' sensory experiences? We show why the answer to both questions is 'no'. Brain function is metabolically costly, and the brain loses some fraction of the information that it encodes and transmits. Therefore, if brains maximize objective functions that increase the fitness of their species, they should adapt to the objective-maximizing rules of the environment at the earliest stages of sensory processing. Consequently, observed 'irrationalities', preferences, and emotions stem from the necessity for our early sensory systems to adapt and process information while considering the metabolic costs and internal states of the organism.

Electrophysiological population dynamics reveal context dependencies during decision making in human frontal cortex

Evidence from monkeys and humans suggests that the orbitofrontal cortex (OFC) encodes the subjective value of options under consideration during choice. Data from non-human primates suggests that these value signals are context-dependent, representing subjective value in a way influenced by the decision makers' recent experience. Using electrodes distributed throughout cortical and subcortical structures, human epilepsy patients performed an auction task where they repeatedly reported the subjective values they placed on snack food items. High-gamma activity in many cortical and subcortical sites including the OFC positively correlated with subjective value. Other OFC sites showed signals contextually modulated by the subjective value of previously offered goods-a context dependency predicted by theory but not previously observed in humans. These results suggest that value and value-context signals are simultaneously present but separately represented in human frontal cortical activity.

Worth the Work? Monkeys Discount Rewards by a Subjective Adapting Effort Cost

All life must solve how to allocate limited energy resources to maximize benefits from scarce opportunities. Economic theory posits decision makers optimize choice by maximizing the subjective benefit (utility) of reward minus the subjective cost (disutility) of the required effort. While successful in many settings, this model does not fully account for how experience can alter reward-effort trade-offs. Here, we test how well the subtractive model of effort disutility explains the behavior of two male nonhuman primates (Macaca mulatta) in a binary choice task in which reward quantity and physical effort to obtain were varied. Applying random utility modeling to independently estimate reward utility and effort disutility, we show the subtractive effort model better explains out-of-sample choice behavior when compared with parabolic and exponential effort discounting. Furthermore, we demonstrate that effort disutility depends on previous experience of effort: in analogy to work from behavioral labor economics, we develop a model of reference-dependent effort disutility to explain the increased willingness to expend effort following previous experience of effortful options in a session. The result of this analysis suggests that monkeys discount reward by an effort cost that is measured relative to an expected effort learned from previous trials. When this subjective cost of effort, a function of context and experience, is accounted for, trial-by-trial choices can be explained by the subtractive cost model of effort. Therefore, in searching for net utility signals that may underpin effort-based decision-making in the brain, careful measurement of subjective effort costs is an essential first step.SIGNIFICANCE STATEMENT All decision-makers need to consider how much effort they need to expend when evaluating potential options. Economic theories suggest that the optimal way to choose is by cost-benefit analysis of reward against effort. To be able to do this efficiently over many decision contexts, this needs to be done flexibly, with appropriate adaptation to context and experience. Therefore, in aiming to understand how this might be achieved in the brain, it is important to first carefully measure the subjective cost of effort. Here, we show monkeys make reward-effort cost-benefit decisions, subtracting the subjective cost of effort from the subjective value of rewards. Moreover, the subjective cost of effort is dependent on the monkeys' experience of effort in previous trials.

Critical tests of fuzzy trace theory in brain and behavior: uncertainty across time, probability, and development

Uncertainty permeates decisions from the trivial to the profound. Integrating brain and behavioral evidence, we discuss how probabilistic (varied outcomes) and temporal (delayed outcomes) uncertainty differ across age and individuals; how critical tests adjudicate between theories of uncertainty (prospect theory and fuzzy-trace theory); and how these mechanisms might be represented in the brain. The same categorical gist representations of gains and losses account for choices and eye-tracking data in both value-allocation (add money to gambles) and risky-choice tasks, disconfirming prospect theory and confirming predictions of fuzzy-trace theory. The analysis is extended to delay discounting and disambiguated choices, explaining hidden-zero effects that similarly turn on categorical distinctions between some gain and no gain, certain gain and uncertain gain, gain and loss, and now and later. Bold activation implicates dorsolateral prefrontal and posterior parietal cortices in gist strategies that are not just one tool in a grab-bag of cognitive options but rather are general strategies that systematically predict behaviors across many different tasks involving probabilistic and temporal uncertainty. High valuation (e.g., ventral striatum; ventromedial prefrontal cortex) and low executive control (e.g., lateral prefrontal cortex) contribute to risky and impatient choices, especially in youth. However, valuation in ventral striatum supports reward-maximizing and gist strategies in adulthood. Indeed, processing becomes less "rational" in the sense of maximizing gains and more noncompensatory (eye movements indicate fewer tradeoffs) as development progresses from adolescence to adulthood, as predicted. Implications for theoretically predicted "public-health paradoxes" are discussed, including gist versus verbatim thinking in drug experimentation and addiction.

Experiential values are underweighted in decisions involving symbolic options

Standard models of decision-making assume each option is associated with subjective value, regardless of whether this value is inferred from experience (experiential) or explicitly instructed probabilistic outcomes (symbolic). In this study, we present results that challenge the assumption of unified representation of experiential and symbolic value. Across nine experiments, we presented participants with hybrid decisions between experiential and symbolic options. Participants' choices exhibited a pattern consistent with a systematic neglect of the experiential values. This normatively irrational decision strategy held after accounting for alternative explanations, and persisted even when it bore an economic cost. Overall, our results demonstrate that experiential and symbolic values are not symmetrically considered in hybrid decisions, suggesting they recruit different representational systems that may be assigned different priority levels in the decision process. These findings challenge the dominant models commonly used in value-based decision-making research.

Nudging Strategies for Arable Land Protection Behavior in China

Arable land protection is critical to the sustainable development of agriculture in China and acceleration of the realization of the trinity protection goal of the quantity, quality, and ecology of arable land. As a new program of behavioral science to promote social development, nudge has gradually gained the favor of researchers and policy makers due to its unique advantages of small cost and substantial effect. However, current research and practical exploration of arable land protection behavior intervention based on the idea of nudging are still lacking. Implicit nudging strategies directly target the heuristic and analytic systems of arable land protection behavior of each stakeholder and possess more advantages than traditional intervention strategies. Therefore, this article designs six arable land protection behavior nudging strategies from the perspectives of cognition and motivation to realize the theoretical discussion of "generating medium-scale returns with nano-level investment". The nudging strategies of the cognitive perspective include default options, framing effects, and descriptive norms, while those of the motivation perspective aim to stimulate home and country, and heritage and benefit motives to promote arable land protection behavior of various stakeholders. The utility of nudge to arable land protection behavior may be controversial in practice. Therefore, the implementation in China should be based on the division of farmers, the number of options should be appropriate, and the external environment of arable land protection behavior should be fully considered.